Through-process Modelling Research Articles

Data-driven through-process modelling of aluminum extrusion: Predicting mechanical properties

This paper reports on a case study on zero-defect manufacturing, using a data driven approach for predicting final product properties from material and manufacturing process information. The case is a company that produces aluminum automotive parts, having an integrated value chain from casting, extrusion, forming and component assembly. This value chain is unique in terms of the intervened and interdependent system of material, process and product properties, where the traditional scientific approach has been to apply physics-based, through-process models to explain the complex thermo-mechanical evolution. Here, an alternative and complementary data-driven model is trained and tested on process data for a 6xxx-alloy product range using machine learning, which then is compared to a physics-based as well as a simple hybrid model. The presented results indicate that a machine learning approach is advantageous when numerous relevant observations are available, inherently adapting to the specific company-level conditions. The main strengths of a physics-based model, on the other hand, is general applicability and self-sufficiency with no need of prior observations.

Combined Gleeble physical welding simulation and low-cycle thermo-mechanical fatigue for heat-affected zone material for 9Cr steel: Experimental testing and through-process model

Combined Gleeble physical welding simulation and low-cycle thermo-mechanical fatigue for heat-affected zone material for 9Cr steel: Experimental testing and through-process model

CAROUSEL: An Open-Source Framework for High-Throughput Microstructure Simulations

High-throughput screening (HTS) can significantly accelerate the design of new materials, allowing for automatic testing of a large number of material compositions and process parameters. Using HTS in Integrated Computational Materials Engineering (ICME), the computational evaluation of multiple combinations can be performed before empirical testing, thus reducing the use of material and resources. Conducting computational HTS involves the application of high-throughput computing (HTC) and developing suitable tools to handle such calculations. Among multiple ICME methods compatible with HTS and HTC, the calculation of phase diagrams known as the CALPHAD method has gained prominence. When combining thermodynamic modeling with kinetic simulations, predicting the entire history of precipitation behavior is possible. However, most reported CALPHAD-based HTS frameworks are restricted to thermodynamic modeling or not accessible. The present work introduces CAROUSEL—an open-sourCe frAmewoRk fOr high-throUghput microStructurE simuLations. It is designed to explore various alloy compositions, processing parameters, and CALPHAD implementations. CAROUSEL offers a graphical interface for easy interaction, scripting workflow for advanced simulations, the calculation distribution system, and simulation data management. Additionally, CAROUSEL incorporates visual tools for exploring the generated data and integrates through-process modeling, accounting for the interplay between solidification and solid-state precipitation. The application area is various metal manufacturing processes where the precipitation behavior is crucial. The results of simulations can be used in upscale material models, thus covering different microstructural phenomena. The present work demonstrates how CAROUSEL can be used for additive manufacturing (AM), particularly for investigating different chemical compositions and heat treatment parameters (e.g., temperature, duration).

Fatigue life assessment in notched injection-molded specimens of a short-glass fiber reinforced Polyamide 6 with different injection gate locations

Based on a previously published Through Process Modeling (TPM) for multiaxial fatigue life assessment of injection-molded components, this work aimed to capture the difference of fiber orientation distribution ahead of notch tips in flat notched samples of PA6GF30 tested in tension at ambient temperature. The fiber orientation originated from different locations of the injection gate for an unchanged macroscopic geometry. Good lifetime estimations were obtained in Side- (resp. Top-) injected samples, regardless the choice of the sample type from which the fatigue criterion was identified. The experimentally observed differences of crack initiation zones were correlated to numerical simulations.

Through-Process Finite Element Modeling for Warm Flanging Process of Large-Diameter Aluminum Alloy Shell of Gas Insulated (Metal-Enclosed) Switchgear.

The large diameter metal shell component (LDMSC) is an important part of gas insulated (metal-enclosed) switchgear (GIS). The LDMSC with multi branches is filled with gas under certain pressure. The plastic forming process is an efficient approach to manufacturing the high reliability LDMSC. The warm flanging process has been widely used to form LDMSC using aluminum alloy. The forming process is characterized by local heating, and the distribution of temperature is strongly inhomogeneous. Although the wall thickness of the shell is 10 mm to 20 mm, the ratio of outer diameter to thickness is more than 40. These present some difficulties in the flanging process and result in some forming defects. Detailed forming characteristics are hard to obtain by analytical and experimental methods. Thus, the through-process finite element (FE) modeling considering heating, forming, unloading, and cooling is one of the key problems to research the manufacturing process of LDMSC. In this study, the through-process FE modeling of the warm flanging process of LDMSC using aluminum alloy was carried out based on the FORGE. The thermo-mechanical coupled finite element method was adopted in the modeling, and the deformation of the workpiece and the die stress were considered together in the modeling. A full three-dimensional (3D) geometry was modeled due to inhomogeneous distribution in all directions for the temperature field. The simulation data of local flame heating could be transferred seamlessly to the simulations of the deforming process, the unloading process, and the cooling process in the through-process FE model. The model was validated by comparison with geometric shapes and forming defects obtained from the experiment. The developed FE model could describe the inhomogeneous temperature field along circumferential, radial, and axial directions for the formed branch as well as the deformation characteristic and the unloading behavior during the warm flanging process. By using the FE model, the forming defects during the flanging process and their controlling characteristics were explored, the evolution of the temperature field through the whole process was studied, and deformation and springback characteristics were analyzed. The results of this study provide a basis for investigating deformation mechanisms, optimizing processes, and determining parameters in the warm flanging process of a large-diameter aluminum alloy shell component.

Fatigue life assessment of a Short Fibre Reinforced Thermoplastic at high temperature using a Through Process Modelling in a viscoelastic framework

A Through Process Modelling (TPM) fatigue life assessment methodology – previously validated in an elastic framework for Short Fibre Reinforced Thermoplastics at room temperature – was extended to high temperature. The viscoelasticity of the matrix was taken into account to estimate the local effective mechanical properties at any point, from the knowledge of local fibre orientation provided by the simulation of injection-moulding. Lifetime estimation was obtained from an energetic fatigue criterion applied in the stationary regime. The approach was validated from uniaxial fatigue tests conducted at 110 °C in tension, on PA66GF30 samples cut out from injected plates with three different orientations to the injection direction, at two stress ratios (0.1 and −1).

Through-process modeling and experimental verification of titanium carbonitride coating prepared by moderate temperature chemical vapor deposition

In this work, the impact of temperature, pressure and gas flow on the chemical compositions, phases and deposition rates of MTCVD (Moderate Temperature Chemical Vapor Deposition) Ti(C,N) coatings is investigated by integrating thermodynamic calculations and computational fluid dynamics (CFD) simulations with key experiments. The thermodynamic calculations predict that both the C and the N contents of the films increase with increasing temperature under constant mixed gases and pressure, with the former increasing faster than the latter. CFD simulations indicate that the coating deposition rate decreases with increasing distance to the source gas for the hard metal samples loaded on the same tray. Subsequently, MTCVD-Ti(C,N) coatings were deposited at three different temperatures to verify the predicted chemical compositions and deposition rates. The experimental investigations are in reasonable agreement with the theoretical predictions. The present work applies a well-established strategy to meet the requirements of a controlled and robust process for MTCVD-Ti(C,N) coating with industrial applications.

Prediction for the mechanical property of short fiber-reinforced polymer composites through process modeling method

The fiber-reinforced polymer composites are important alternative for conventional structural materials because of their excellent comprehensive performance and weight reduction. The mechanical properties of such composite materials are mainly determined by the fiber orientation induced through practical manufacturing process. In the study, a through process modeling (TPM) method coupling the microstructure evolution and the mechanical properties of fiber-reinforced composites in practical processing is presented. The numerical methodology based on the finite volume method is performed to investigate three-dimensional forming process in the injection molding of fiber-reinforced composites. The evolution of fiber orientation distribution is successfully predicted by using a reduced strain closure model. The corresponding finite volume model for TPM is detailedly derived and the pressure implicit with splitting of operators (PISO) algorithm is employed to improve computational stability. The flow-induced multilayer structure is successfully predicted according to essential flow characteristics and the fiber orientation distribution. The mechanical properties of such anisotropy composites is further calculated based on the stiffness analysis and the Tandon–Weng model. The improvement of mechanical properties in each direction of the injection molded product are evaluated by using the established mathematical model and numerical algorithm. The influences of the geometric structure of injection mold cavity, the fiber volume fractions, and the fiber aspect ratios on the mechanical properties of composite products are further discussed. The mathematical model and numerical method proposed in the study can be successfully adopted to investigate the structural response of composites in practical manufacturing process that will be helpful for optimum processing design.

Through process Modeling applied to the fatigue design of cast A356-T6 components

The optimization of cast aluminum alloy components is proposed using a Through Process Modeling (TPM) methodology applied to the fatigue design. A full manufacturing process simulation of a cast aluminum alloy A356 component is described. The modeling strategy presented in this paper is able to simulate the defect size, microstructure size and thermal history during the casting process. The microstructure and defect simulated are the Secondary Dendrite Arm Spacing (SDAS) and maximum pore size, respectively. Based on the Defect Stress Gradient approach (DSG) published in a previous work, the fatigue limit is predicted as a function of the SDAS and defect size. Tension fatigue tests have been performed on bespoke prototype cast component samples with various SDAS and defect size. The comparison between experimental results and the TPM simulation shows good agreement in terms of simulated heat transfer rates, defect size, SDAS and fatigue limit except for defect sizes greater than 500 µm.

Through-process modelling of welding and service of 9Cr steel power plant components under load-following conditions

This paper is concerned with the development of a through-process model to predict the in-service performance of high-temperature, 9Cr steel, power plant components. A multi-pass welding simulation is conducted using the finite element software Abaqus. A user-material subroutine, including microstructure evolution and a physically-based constitutive model, is employed to predict the mechanical response of the material during welding and to predict welding residual stresses. Points are sampled from the FE geometry and their microstructure parameters and residual stress values are used in a uniaxial code to predict the relative in-service lives of the different weld regions under load-following power plant operating conditions. It is shown that post-weld heat treatment significantly improves predicted life and that there is a strong correlation between predicted microstructure before service and the predicted in-service life.

Through-Process Modelling for Accurate Prediction of Long Term Anisotropic Mechanics in Fibre Reinforced Thermoplastics.

Fibre reinforced thermoplastic (FRTP) materials offer great potential for, among others, weight and cost reduction in a wide range of applications. In this paper, consequences of fiber orientation-induced anisotropy (due to injection molding process) in the development of FRTP parts as well as predictive engineering techniques for part performance evaluation are discussed. A coupled simulation methodology will be used to predict the processing-microstructure-properties relation in FRTP parts, thereby enabling the ability to include fiber orientation-induced anisotropy. In parallel, long term fatigue data was collected on increasingly complex geometries for the purpose of model validation.

Modelling of the Age-Hardening Behavior in AA6xxx within a Through-Process Modelling Framework

The manufacturing of AA6xxx car body panels typically consists of rolling, ageing and forming processes. Thus, multiple simulation tools can be coupled to set up a through-process modelling (TPM) framework for predicting the evolution of microstructure and the final mechanical properties of these products. In order to realize such a TPM concept, various industrial processing phenomena were studied and modelled in the open innovation research cluster “Advanced Metals and Processes” (AMAP♯). This work focuses on the age hardening behavior which takes place during the industrial paint bake process. To reflect the microstructure evolution of this processing step, a multi-component precipitation model is developed. So far, the influences of thermomechanical processes, i.e. annealing temperature on the kinetics of MgxSiy precipitates during artificial aging were implemented. The precipitation model was linked to a yield strength model in order to simulate the evolution of mechanical properties within the TPM framework. For validation, the evolution of microstructure and mechanical properties of an AA6016 alloy during artificial ageing was investigated via transmission electron microscopy (TEM) and tensile testing. The simulation results are in agreement with experimental observations.

Through-Process Modeling of Microstructure Development during Multi-Pass Hot Deformation Including Partial Recrystallization

During reversible break-down hot rolling, recrystallization can take place during inter-pass annealing and even after the final pass, because the material is kept at high temperature throughout the process. A partially recrystallized microstructure is quite often obtained during inter-pass annealing and is the starting state for the subsequent rolling pass. This is in particular the case when fine particles are already present or have just precipitated in the microstructure. The particles can pin the moving grain boundaries in the hot deformed material with low energy stored during deformation. To transfer the partly recrystallized microstructure from the recrystallization model to the deformation model for simulation of the subsequent pass, a new link method has been developed for multi-pass through-process modeling. This method allows a direct data flow between the deformation model GIA-3IVM+ and the recrystallization model CORe. This new model framework was used to simulate the microstructure evolution during break-down hot rolling of precipitates containing alloy AA6016. The predicted microstructure agrees well with experimental observations.

Influence of Microstructure Representation on Flow Stress and Grain Size Prediction in Through-Process Modeling of AA5182 Sheet Production

Integrated computational materials engineering is an up to date method for developing new materials and optimizing complete process chains. In the simulation of a process chain, material models play a central role as they capture the response of the material to external process conditions. While much effort is put into their development and improvement, less attention is paid to their implementation, which is problematic because the representation of microstructure in the model has a decisive influence on modeling accuracy and calculation speed. The aim of this article is to analyze the influence of different microstructure representation concepts on the prediction of flow stress and microstructure evolution when using the same set of material equations. Scalar, tree-based and cluster-based concepts are compared for a multi-stage rolling process of an AA5182 alloy. It was found that implementation influences the predicted flow stress and grain size, in particular in the regime of coupled hardening and softening.

Phase-field modelling of microstructure evolution during processing of cold-rolled dual phase steels

AbstractCold-rolled dual-phase steels, which belong to the advanced high strength steels, have gained much interest within the automotive industry. The formation of dual-phase microstructure, which provides an optimal combination of strength and formability for automotive applications, occurs during intercritical annealing of cold-rolled strip. Variations in the chemical composition as well as in the heat treatment parameters influence very strongly the microstructure development and therefore the final mechanical properties of the strip. Thus, the precise control of the microstructure evolution during full processing route is required for the achievement of essential mechanical properties. The current work is focused on a through-process model on a microstructural scale for the production of dual-phase steel from cold-rolled strip, which is based on Phase-Field Method and combines the description of ferrite recrystallisation and all phase transformations occurring during intercritical annealing. This approach will enable the prediction of final microstructure for varying composition and processing conditions, and therefore, can be used for the process development and optimisation.

Control of texture and earing in aluminium alloy AA 3105 sheet for packaging applications

The development of crystallographic texture upon the thermo-mechanical processing of aluminium sheet may result in the formation of pronounced plastic anisotropy and, especially, give rise to the known earing phenomenon. In the present paper two industrial process routes for controlling the texture and, therewith, reduce earing in Al strip for packaging products are compared. High-strength material with low earing properties is obtained by heavy cold rolling of hot strip with a pronounced cube texture (H19 route). Medium strength sheet with very low earing is achieved by the addition of an intermediate annealing before a light final rolling pass (H16 route). The set-up of a comprehensive through-process model of the evolution of microstructure, texture and resulting earing properties during the thermo-mechanical processing of Al sheet requires the combination of suitable models for simulating the evolution of microstructure and texture during the various process steps involved. With the help of these coupled models the most important effects regarding texture and texture-related properties can be reproduced. This yields valuable information on the evolution of earing as a function of process parameters that can be utilized to understand and eventually improve the quality of aluminium sheet products under minimization of laborious and expensive plant trials.

On the Impact of Thermo-Mechanical Processing on Texture and the Resultant Anisotropy of Aluminium Sheet

During the thermo-mechanical processing of aluminium sheet products in commercial production lines the material experiences a complex history of temperature, time and strain paths, which result in alternating cycles of deformation and recrystallization with the associated changes in microstructure and, especially, crystallographic texture. Thus, computer-based alloy and process development requires integration of models for simulat¬ing the evolution of microstructure, microchemistry and crystallographic texture into process models of the thermo-mechanical production of Al sheet. In the present paper the influence of texture on the anisotropic properties is explored for various industrially processed aluminium alloy sheets for packaging applications. Besides the use of experimentally measured sheet textures as an input for the anisotropy calculations, particular attention is given to the use of modelled textures. Here, results from a comprehensive through-process modelling of the texture evolution during the thermo-mechanical production of aluminium sheet are utilized. Eventually, this will enable us to predict the evolution of texture and the resulting properties along the entire process chain and hence to improve product quality of aluminium sheet products avoiding laborious and expensive plant trials.

Through-process sensitivity analysis on the effect of process variables on strength in extruded Al–Mg–Si alloys

A concept of through-process modelling for studying the effect of process variables on the strength of extruded Al–Mg–Si alloys is presented. Five models are integrated to model casting, homogenisation, extrusion and ageing of the alloys. It is demonstrated that through-process modelling can be utilised to study isolated effects from variations in processing parameters along the value chain on the strength in the end product, which is usually difficult to obtain from experiments. In the present work it has been focused on strength after artificial ageing and the most critical parameters to follow were therefore the Mg and Si and whether these elements appear in solid solution or present in constituent phases. The as-cast and homogenised structures were predicted reasonably well by the models, and it was found that the casting parameters have a significant influence on the density of constituent particles. Chemical composition and cooling rate from extrusion temperature are the variables with the most prominent effect on the yield stress of extruded and aged sections.

Multiaxial fatigue life assessment for reinforced polymers

The multiaxial fatigue behaviour of PBT–PET GF30 (polybutylene terephthalate–polyethylene terephthalate with 30% mass short glass fibres) and PA66 GF35 (Polyamide 66 with 35% mass short glass fibres) is studied under constant amplitude force loading. Standard flat specimens are used to establish the influence of microstructure on the tension fatigue behaviour. Tubular specimens are used to study the influence of loading path on the tension–torsion fatigue behaviour. Finally an experimental device is developed to test dedicated flat samples in order to study the influence of microstructure on the pure shear fatigue behaviour. All fatigue tests are performed at two load ratios: −1 and 0, 1. Experimental results are analysed using a Through Process Modelling (TPM) based on three major steps. The first one is based on the simulation of the whole process in order to get the fibre orientation tensor at each point of the part. The second one uses the orientation tensor to perform a two-step homogenization procedure in order to estimate local effective properties and compute the stress–strain response as a function of local anisotropy. Mechanical fields thus obtained are used as input data for the application of a fatigue criterion in the third step. Results show that energetic fatigue criterion is an excellent compromise to get good fatigue life assessment for only one experimental input fatigue data.

Effect of Material Property Changes on the Performance of Al Rolling Mills

The industrial production of aluminium strip comprises a rather long process chain. One of the characteristics of aluminium alloys is that a number of final strip properties are influenced considerably already at very early process stages. Since it is practically impossible to run large variations of controlled process changes on an industrial mill experimentally, Through Process Modelling (TPM) has been in focus of research and has developed into a valuable tool to design process chains with a view to achieving desired properties. Metallurgical models in combination with (plasto-) mechanical/thermal models trace variables of state through the process chain down to the final operation. However, there are further important properties of the product, which may be generated as consequence of the total production history. Predominant examples are the strip profile and flatness and the product surface. These properties do not only result from the processes settings, they may also have a strong back-effect on the process performance itself. As a consequence they may also affect the metallurgical properties. This paper shows representative computations of in-dustrial aluminium rolling process steps to evaluate the interactions of different mechanisms taking place in the rolling processing chain, with a special attention to profile/flatness, surface and metal-lurgical properties.